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Physiologically based pharmacokinetic model outputs depend on dissolution data and their input

Case examples glibenclamide and dipyridamole
: Klumpp, L.; Dressman, J.


European journal of pharmaceutical sciences : EUFEPS 151 (2020), Art.105380
ISSN: 0928-0987
ISSN: 1879-0720
Fraunhofer IME ()

A plethora of dissolution tests exists for oral dosage forms, with variations in selection of the dissolution medium, the hydrodynamics and the dissolution equipment. This work aimed at determining the influence of media composition, the type of dissolution test and the method for entering the data into a PBPK model on the ability to simulate the in vivo plasma profile of an immediate release formulation. Using two rDCS IIa substances, glibenclamide and dipyridamole, housed in immediate-release formulations as model dosage forms, dissolution tests were performed in USP apparatus II with the biorelevant media FaSSGF, FaSSIF V1, V2 and V3 using both single-stage and two-stage test designs. The results were then integrated into the PBPK software SimcypⓇ either as the observed release profile (dissolution rate model, DRM) or using a semi-mechanistic model (diffusion layer model, DLM) and compared with in vivo plasma profiles. The selection of the FaSSIF version did not appear to have any relevant influence on the dissolution of the weakly basic dipyridamole, while the weakly acidic glibenclamide was sensitive to the difference in pH between FaSSIF V1, V2 and FaSSIF V3. Since both compounds have pKa values close to the pH of biorelevant media representing conditions in the small intestine, these results may be specific to compounds with similar ionization behavior. Single-stage and two-stage testing led to equivalent simulations for glibenclamide. Only results from the single-stage test in FaSSGF led to a close simulation of the pharmacokinetic profile of dipyridamole when data were inputted using the DRM, while simulations from two-stage testing were most similar to the observed pharmacokinetic profile when DLM with selection of a dynamic pH profile in the small intestine was selected as the data input method. These results emphasize the importance of data input to the simulation results.